A case of autologous microfat grafting in lip reconstruction of a whistle deformity following cancer treatment
Bibliographic record
Abstract
Case PresentationA 61-year-old man developed a squamous cell carcinoma on his left lower lip, which was initially excised with positive margins.He subsequently developed lymphadenopathy within the left neck and was referred to the Division of Otolaryngology -Head and Neck Surgery at the Queen Elizabeth II Health Sciences Centre (Halifax, Nova Scotia).He underwent a second wedge resection of the left lower lip with an ipsilateral functional neck dissection.The patient received postoperative radiotherapy to the lip and neck at a total dose of 66 Gy.As a result of his combined modality treatment, he developed a whistle deformity, marked by lip incontinence and an asymmetric smile, and was referred to another member of the head and neck team who was an expert in facial plastic surgery for potential fat augmentation and reconstruction of his lower lip (Figure 1).It was decided that the patient would receive hyaluronic acid-based injectable tissue filler for temporary augmentation, followed by treatment with autologous microfat transplantation to the lip for definitive augmentation.Following the tissue filler injection, it was noted that the patient had closure of the lateral lip margin, improvement in lip competence and a pleasing aesthetic result.However, on reassessment three months later, the patient reported having issues of lip incompetence, once again, due to the relatively premature degradation of the tissue filler and subsequent reformation of his whistle deformity.A decision was then made to proceed with autologous microfat transplantation to the lip.The donor site chosen by the senior author was the abdomen, and a series of three injections was CAse report©2010 Pulsus Group Inc.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.014 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".